1. Field of the Invention
The present invention relates to a technology for retrieving a pattern image.
2. Description of the Related Art
In a manufacturing field, to develop a competitive product at low costs and to introduce the product into markets as early as possible, it is desirable to effectively utilize technical resources such as drawings of existing products. To find out necessary information from among a large number of drawings that have been accumulated, a retrieving technique that can efficiently retrieve a drawing including necessary parts is necessary.
In a simple method, retrieval has been performed mainly based on texts by using a part name provided to a drawing as a key word. Recently, to retrieve a part having a shape difficult to be expressed only with texts, a similar-pattern retrieving in which the retrieval is performed using pattern information of a part depicted in a drawing is also getting popular. Such a technology is disclosed in, for example, Technology and Research Report of Electronic Information and Communication Association, PRMU2004-225, pp. 79-84 (2005), titled “Proposal of Part Retrieval Approach Based on Patterns Obtained from Machine System Assembly Drawings” by Baba, Liu Rujie, Endo, Shiitani, Uehara, Masumoto, and Nagata; Proc. of IAPR Workshop on Document Analysis Systems (DASO4), September 2004, pp. 378-388, “Attributed Graph Matching Based Engineering Drawings Retrieval” by Liu Rujie, Baba, and Masumoto; and Proc. of the IEE International Conference on Visual Information Engineering: Convergence in Graphics and Vision (VIE2005), April 2005, pp. 45-50) titled “Component Parts Extraction from Assembly Drawings for Content Based Retrieval” by Liu Rujie, Baba, and Masumoto.
In the above technique, predetermined types of features are prepared in advance for information such as a pattern extracted from drawings. However, the features to be utilized in retrieving have to be designated by a user in a trial-and-error manner.
If a designated feature is not appropriate, precision of retrieval is degraded. If a desired pattern can not be retrieved, another feature has to be designated again to repeat the retrieval. Thus, the retrieval requires much time.
In the conventional method for designating a query image in the similar-pattern retrieving, as a query image to be designated first by a user, an image called “representative query image” is prepared for each roughly classified type (genre), such as bolt or nut, of drawing.
In such similar-pattern retrieval, empirically obtained knowledge cannot be effectively utilized even when it is empirically known that higher retrieval precision can be obtained using a different type of feature depending on a representative query image. For example, even when it is understood that higher retrieval precision can be respectively obtained using feature a for a representative query image A, and using feature b for a representative query image B, there is no mechanism in the conventional similar-pattern retrieval to utilizes such information.
Therefore, when a new query image α is given, a feature to be used has to be designated by a user in a trial-and-error manner without utilizing the empirically obtained information.